In numerous applications, such as recognizing images, for example, it is desired to extract characteristics from digital images in order to discriminate between them.
Methods of detecting points of interest or “salient” points in an image are known for this purpose, for example from reference [6]. Such points of interest are points containing a large amount of information and they can be situated, for example, on the outlines of shapes present in the image. These points of interest can be defined as being points corresponding to high frequency zones in the image.
Several techniques are known for characterizing images.
Thus, a first category of techniques categorize color, e.g. using an autocorrelogram or a color histogram, as in references [7], [8], [9], mentioned below.
In a second category, according to reference [10] mentioned below, texture is characterized with the help of Gabor filters.
Finally, in a third category, according to reference [11] mentioned below, form is characterized with the help of a histogram of orientation distribution in the image. An approach of that type is used in the MPEG7 standard.
Those techniques nevertheless present the drawback of not characterizing localized singularities in the image.